Are the well-known facts about urbanization in the United States also true for the developing world? We compare American metropolitan areas with comparable geographic units in Brazil, China and India. Both Gibrat's Law and Zipf's Law seem to hold as well in Brazil as in the U.S., but China and India look quite different. In Brazil and China, the implications of the spatial equilibrium hypothesis, the central organizing idea of urban economics, are not rejected. The India data, however, repeatedly rejects tests inspired by the spatial equilibrium assumption. One hypothesis is that the spatial equilibrium only emerges with economic development, as markets replace social relationships and as human capital spreads more widely. In all four countries there is strong evidence of agglomeration economies and human capital externalities. The correlation between density and earnings is stronger in both China and India than in the U.S., strongest in China. In India the gap between urban and rural wages is huge, but the correlation between city size and earnings is modest. The cross-sectional relationship between area-level skills and both earnings and area-level growth are also stronger in the developing world than in the U.S. The forces that drive urban success seem similar in the rich and poor world, even if limited migration and difficult housing markets make it harder for a spatial equilibrium to develop.

We study the rationality of individual and consensus forecasts of macroeconomic and financial variables using the methodology of Coibion and Gorodnichenko (2015), who examine predictability of forecast errors from forecast revisions. We find that individual forecasters typically overreact to news, while consensus forecasts under-react relative to full-information rational expectations. We reconcile these findings within a diagnostic expectations version of a dispersed information learning model. Structural estimation indicates that departures from Bayesian updating in the form of diagnostic overreaction capture important variation in forecast biases across different series, yielding a belief distortion parameter similar to estimates obtained in other settings. (JEL C53, D83, D84, E13, E17, E27, E47)

We acknowledge support from the Taubman Center for State and Local Government. Chauvin acknowledges support from the Center for International Development at Harvard University. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. At least one co-author has disclosed a financial relationship of potential relevance for this research. Further information is available online at http://www.nber.org/papers/w22002.ack NBER working papers are circulated for discussion and comment purposes. They have not been peerreviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

Macro-finance analyses commonly link firms’ borrowing constraints to the liquidation value of physical assets. For US nonfinancial firms, we show that 20% of debt by value is based on such assets (“asset-based lending” in creditor parlance), whereas 80% is based predominantly on cash flows from firms’ operations (“cash flow–based lending”). A standard borrowing constraint restricts total debt as a function of cash flows measured using operating earnings (“earnings-based borrowing constraints”). These features shape firm outcomes on the margin: first, cash flows in the form of operating earnings can directly relax borrowing constraints; second, firms are less vulnerable to collateral damage from asset price declines, and fire sale amplification may be mitigated. Taken together, our findings point to new venues for modeling firms’ borrowing constraints in macro-finance studies.

for outstanding research assistance. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

Using micro data from Duke University quarterly survey of Chief Financial Officers, we show that corporate investment plans as well as actual investment are well explained by CFOs' expectations of earnings growth. The information in expectations data is not subsumed by traditional variables, such as Tobin's Q or discount rates. We also show that errors in CFO expectations of earnings growth are predictable from past earnings and other data, pointing to extrapolative structure of expectations and suggesting that expectations may not be rational. This evidence, like earlier findings in finance, points to the usefulness of data on actual expectations for understanding economic behavior.

Chinese housing prices rose by over 10 percent per year in real terms between 2003 and 2014 and are now between two and ten times higher than the construction cost of apartments. At the same time, Chinese developers built 100 billion square feet of residential real estate. This boom has been accompanied by a large increase in the number of vacant homes, held by both developers and households. This boom may turn out to be a housing bubble followed by a crash, yet that future is far from certain. The demand for real estate in China is so strong that current prices might be sustainable, especially given the sparse alternative investments for Chinese households, so long as the level of new supply is radically curtailed. Whether that happens depends on the policies of the Chinese government, which must weigh the benefits of price stability against the costs of restricting urban growth.

No abstract